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Forward index

As explained in Natural Language Processing in Action, Second Edition

A forward index maps each document to the words or features it contains.

A forward index lists the words in each document, creating a document-first view of searchable content. It is the starting point for building an inverted index. section 10.3.1

From documents to search

For documents containing “cat” and “cats,” the forward index records each document’s words. Inverting that structure groups each word with the documents containing it, allowing a search for “cat” to jump directly to matches instead of scanning every document. section 10.3.1

A forward index supports the indexing pipeline:

  • List words, and optionally their positions, for every document. section 10.3.1
  • Invert the listings into a word-to-document structure for efficient retrieval. section 10.3.1

How Natural Language Processing in Action, Second Edition covers it

How deep it goes
Defines document-word listings and their inversion, but stops short of detailed implementation or storage design.
Examples
Uses documents containing “cat” and “cats,” word positions, and direct lookup versus document-by-document scanning.
What it assumes
Assumes only basic notions of documents, words, and keyword search.
What you can do after
Evaluate how document-first listings become inverted structures for faster keyword retrieval.
How it connects
Connects forward indexes with inverted indexes, full-text search, trigram indexes, and search engines.

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This explainer was generated by Manning's knowledge graph from the text of Natural Language Processing in Action, Second Edition. The section links point to the parts of the book it draws on.